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Using population metrics to fine-tune your health system

As more and more provider organizations take on the risk associated with attributed populations, they will need to develop capabilities around reviewing and analyzing data.

In my last post, I shared how patient-level metrics can impact quality of care. In this post, I’ll discuss how population-level metrics can help health systems focus on critical needs within their communities, and how the combination of population- and patient-level metrics can improve overall health.

Population-level metrics, also known as system-level metrics, allow provider organizations to identify opportunities that have a broader impact over the entire health system’s operations. With these types of metrics powering a population health management program, organizations can positively impact many more members within the attributed population.

While these high-level population insights aren’t typically useful for individual care, they do help the health system on a macro level. They are quite useful in identifying areas of variation in physician performance and in population characteristics.

With that information in hand, providers have the ability to influence utilization, quality and efficiency of care in wide-ranging, impactful ways, including ways that positively influence the system’s bottom line.

In addition, using population-level metrics will help value-based systems to identify health care delivery processes that are inefficient, highly variable or unnecessary altogether and thus cause financial risk to the overall system.

Many providers don’t have access to the data they need to successfully manage risk, let alone the experience they need to interpret that data. But understanding and interpreting patient- and population-based metrics, as well as other data that supplement their trusted medical record, is a critical skill.

Taken together, these data sets improve providers’ ability to understand the current and future health care needs of their attributed populations.

Joel Hoffman is senior vice president and chief analytics officer of Optum. In this role, he is responsible for the analysis and interpretation of data in support of Optum’s overall market activities and growth, working with strategic clients on innovative opportunities and advancing high-value external priorities, including those with select international and acquisition partners. Joel most recently maintained responsibility for Payer Consulting, an OptumInsight Payer Solution’s business comprised of over 800 professionals focused on facilitating favorable performance and profitable growth for clients while reducing organizational exposure. He graduated Summa Cum Laude from Temple University with a BA in Mathematics. Prior to joining Optum, Joel was a partner at Ernst & Young.